My graduate studies included learning about constraint-based optimization algorithms (such as linear programming) and ...

Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

Each year when MD+DI editors sit down to discuss Medtech Company of the Year prospects, the companies that rise to the top for us tend to be those that have had a transformational year either through ...

Abstract: This article studies distributed optimization problems whose goal is to minimize the sum of cost functions located among agents in a network, where communications are described by a ...

You probably don’t need more time. By Jancee Dunn When I look back on all the major decisions I’ve dithered over, I could scream. It took me a decade to commit to becoming a parent. I wavered for a ...

Search optimization now requires combining traditional SEO with AI-focused GEO and answer-driven AEO strategies AI search usage continues to grow, with 10% of US consumers currently using generative ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

If you want to accentuate the importance of a problem, it seems sensible to explain how prevalent it is. Lots of people are at risk of Alzheimer’s disease. Lots of women carry a gene that makes them ...

Artificial intelligence has witnessed a remarkable surge, captivating researchers, product teams, and end users alike with its transformative potential. But despite its recent popularity, AI is only ...